1 citations · 1 across the 4 of their papers we have counts for
6 papers
NAVER LABS Europe's Multilingual Speech Translation Systems for the IWSLT 2023 Low-Resource Track
Edward Gow-Smith, Alexandre Berard, Marcely Zanon Boito +1
This paper presents NAVER LABS Europe's systems for Tamasheq-French and Quechua-Spanish speech translation in the IWSLT 2023 Low-Resource track. Our work attempts to maximize trans…
DaLC: Domain Adaptation Learning Curve Prediction for Neural Machine Translation
Cheonbok Park, Hantae Kim, Ioan Calapodescu +2
Domain Adaptation (DA) of Neural Machine Translation (NMT) model often relies on a pre-trained general NMT model which is adapted to the new domain on a sample of in-domain paralle…
Machine Translation of Restaurant Reviews: New Corpus for Domain Adaptation and Robustness
Alexandre Bérard, Ioan Calapodescu, Marc Dymetman +3
We share a French-English parallel corpus of Foursquare restaurant reviews (https://europe.naverlabs.com/research/natural-language-processing/machine-translation-of-restaurant-revi…
Naver Labs Europe's Systems for the Document-Level Generation and Translation Task at WNGT 2019
Fahimeh Saleh, Alexandre Bérard, Ioan Calapodescu +1
Recently, neural models led to significant improvements in both machine translation (MT) and natural language generation tasks (NLG). However, generation of long descriptive summar…
Naver Labs Europe's Systems for the WMT19 Machine Translation Robustness Task
Alexandre Bérard, Ioan Calapodescu, Claude Roux
This paper describes the systems that we submitted to the WMT19 Machine Translation robustness task. This task aims to improve MT's robustness to noise found on social media, like…
Moment Matching Training for Neural Machine Translation: A Preliminary Study
Cong Duy Vu Hoang, Ioan Calapodescu, Marc Dymetman
In previous works, neural sequence models have been shown to improve significantly if external prior knowledge can be provided, for instance by allowing the model to access the emb…